Biomedical subjects

Xinyi Li

Publications and source records attributed to Xinyi Li.

4 recordsLinked to original sources

PubMed2026

Dosimetric Parameters of the Heart and Its Substructures in Predicting Cardiac Events or Survival in Patients With Lung Cancer After Radiation Therapy: A Systematic Review and Meta-analysis.

The predictive value of radiation dose to the whole heart (WH) and cardiac substructures (CS) for cardiac events (CEs) and survival in patients with lung cancer remains uncertain. The goal of this study was to conduct a systematic review and meta-analysis to provide an evidence-based estimate of the relationship between these associations. A systematic meta-analysis was performed following PRISMA guidelines. Risk of bias was assessed using the JBI Critical Appraisal Checklist for Case Series. Outcomes were classified into major adverse cardiac events (MACE), arrhythmias, pericardial effusion, and survival. Depending on heterogeneity, random- or fixed-effects models were applied to calculate pooled hazard ratios (HRs) for univariable and multivariable analyses. A total of 80 studies, including 21,645 patients, were analyzed. Of these, 25 studies reported CEs, and 69 reported survival outcomes. Among 91 WH and 215 CS parameters evaluated, several showed significant associations. Key findings from our meta-analysis include: (1) left anterior descending (LAD) V15 was significantly associated with MACE. The mean heart dose (MHD), as well as ventricle and LAD doses, were significantly associated with ischemic events. (2) Multiple CS parameters were associated with different arrhythmia subtypes. (3) MHD, heart V5/V35/V55 and pericardial doses were significantly associated with pericardial effusion. (4) MHD was significantly associated with survival; CS parameters also showed predictive value, and especially, heart base dose being the most significant. (5) We also identified several thresholds with potential predictive values, such as LAD V15 <10% for MACE, left pulmonary vein (LPV) V55 <2%, and right pulmonary vein (RPV) V10 <54% for atrial fibrillation (AF), right atrium (RA) V60 <0.03 cc for non-AF supraventricular tachyarrhythmia, and left main artery (LMA) V10 ≥1 cc for bradyarrhythmia. This study identified 130 WH and CS dosimetric parameters associated with CEs and 131 with survival outcomes. These findings enhance our understanding of radiation-induced heart injury mechanisms and provide guidance for potential protective and intervention strategies.

Humans↗

PubMed2026

In vivo epigenome editing reduces circulating lipids and attenuates atherosclerosis in mice.

Atherosclerotic cardiovascular disease remains the leading cause of global mortality, with hypercholesterolemia serving as a critical driver of atherogenesis. Although current lipid-lowering therapies substantially improve circulating lipid profiles, strategies that provide more durable, safe, and efficient control of lipid metabolism are still needed. Epigenome editing offers a promising approach for long-lasting repression of disease-modifying genes without altering the underlying DNA sequence. Here, we develop CRISPRoff platforms delivered by adeno-associated virus or lipid nanoparticle to epigenetically silence hepatic Hmgcr or Pcsk9 in vivo. In both C57BL/6J wild-type and ApoE-/- mice, CRISPRoff mediates robust and durable repression of these targets, leading to marked reductions in circulating total cholesterol, low-density lipoprotein cholesterol, and triglycerides. In the ApoE-/- context, epigenetic silencing of Pcsk9 confers pronounced vascular protection, including decreased lipid accumulation in the liver and aortic root, reduced necrotic core formation, diminished macrophage infiltration, and enhanced plaque stability. Together, these results provide proof of principle that CRISPRoff-based epigenome editing enables stable repression of clinically relevant targets and ameliorates key features of atherosclerotic disease. This work lays the foundation for broader therapeutic applications of epigenetic modulation in cardiovascular disorders.

Animals↗

PubMed2025

Screening of the key single nucleotide polymorphisms in type 2 diabetes mellitus complicated with lower extremity arterial disease by machine learning.

OBJECTIVES: Diabetic lower extremity arterial disease (LEAD) is a manifestation of diabetic lower extremity vascular complications. This study aimed to screen the key single nucleotide polymorphism (SNP) gene signature in patients with type 2 diabetes mellitus (T2DM) and LEAD. METHODS: A total of 147 patients with T2DM complicated by LEAD and 144 patients with T2DM without LEAD were enrolled for transcriptome sequencing. The Plink software was used to preprocess the data. Five machine learning methods were adopted to build the SNP diagnosis models. The receiver operating characteristic (ROC) curve was used to quantify the predicted probabilities of the model. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the cluster Profiler package. Finally, regression statistical analysis was used to correlate the key SNPs with clinical information and biochemical indicators. RESULTS: A total of 24 SNPs were retained and 10 SNPs were risk allele genes. Nine SNPs (rs7412, rs1800629, rs699947, rs3918242, rs668, rs1800470, rs1800449, rs1800469, and rs1024611) were identified as the key SNPs sites. GO and KEGG pathway analyses revealed that these genes are mainly enriched in fluid shear stress and atherosclerosis. Finally, rs1800449 was associated with low-density lipoprotein cholesterol (LDL-C). With high density lipoprotein cholesterol (HDL-C), related site was rs1024611. The sites associated with total cholesterol (CHOL) were rs1800449 and rs7412.The site associated with apolipoprotein B (APOB) and apolipoprotein A1 (APOA1) were rs1800470 and rs1800469. CONCLUSION: This study authenticated nine SNPs for the diagnosis of T2DM patients with LEAD, which will be of great significance in the development of diagnostic molecular biomarkers for T2DM patients.

Humans↗

PubMed2025

Cytotype classification and genetic diversity of Platostoma palustre revealed by rDNA localization and chloroplast genome.

BACKGROUND: Platostoma palustre A. J. Paton is an edible medicinal plant that plays a significant role in traditional food production and medicinal applications. However, the genetic basis of P. palustre remains unclear, thereby hampering research on its genome and polyploid evolution. RESULTS: To characterize the karyotype and ploidy of P. palustre, we performed fluorescence in situ hybridization (FISH) by using 35 S and 5 S rDNA probes in P. palustre. FISH results indicated that 35 S rDNA mapped to the end of the chromosome (chromosome satellite, heterochromatic region) and that 5 S rDNA was located close to the centromere of the chromosomes. Based on the rDNA sites, we identified three distinct cytotypes of P. palustre: diploid (2n = 2x = 30, x = 15), triploid (2n = 3x = 45, x = 15), and tetraploid (2n = 4x = 60, x = 15). To further explore the genetic evolutionary relationship among these P. palustre cytotypes, we conducted Illumina sequencing and assembled the chloroplast (CP) genome. The CP genomes of P. palustre accessions maintained a conserved single circular molecule with a length of 152,534 - 152,788 bp, comprising a large single-copy region (LSC) and small single-copy region (SSC) separated by two inverted repeat regions (IRs). Phylogenetic trees were also created based on CP and nuclear molecular markers, showing that most P. palustre accessions clustered together corresponding to their collection regions. Of these, GDZC2 (2n = 2x = 30) clustered with several triploid accessions, suggesting that it may share a common ancestor with these triploid accessions. CONCLUSIONS: This is the first study to characterize the karyotype, identify three cytotypes of P. palustre using FISH, and provide molecular evidence for an evolutionary relationship among different P. palustre accessions. These findings will be useful for further genomic studies and polyploid evolution of P. palustre.

Genome, Chloroplast↗